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Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR) = 1.15, 95% CI = 1.07 to 1.23, P = 7.8 × 10− 5) and diabetes (OR = 1.43, 95% CI = 1.31 to 1.56, P = 9.4 × 10− 15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR = 0.87, 95% CI = 0.78 to 0.97, P = 0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.

Background The prevalence of atrial fibrillation (AF) is increasing with an aging worldwide population, yet a comprehensive understanding of its causes and consequences remains limited. We aim to assess the causes and consequences of AF via a bidirectional Mendelian randomization (MR) analysis. Methods We used publicly available genome-wide association study (GWAS) summary data, centralized and harmonized by an open GWAS database. We assessed the genetically predicted effects of 5048 exposures on risk of AF, and the genetically predicted effects of genetic liability to AF, on 10 308 outcomes via two-sample MR analysis. Multivariable MR analysis was further conducted to explore the comparative roles of identified risk factors. Results MR analysis suggested that 55 out of 5048 exposure traits, including four proteins, play a causal role in AF (P Conclusions Our results suggest body mass index, height, systolic blood pressure and genetic liability to coronary artery disease are independent causal risk factors for AF. Several proteins, including DUSP13, IL-6R and TNFSF12, may have therapeutic potential for AF.

Background and aims Observational studies have linked elevated blood pressure (BP) to impaired cognitive function. However, the functional and structural changes in the brain that mediate the relationship between BP elevation and cognitive impairment remain unknown. Using observational and genetic data from large consortia, this study aimed to identify brain structures potentially associated with BP values and cognitive function. Methods and results Data on BP were integrated with 3935 brain magnetic resonance imaging-derived phenotypes (IDPs) and cognitive function defined by fluid intelligence score. Observational analyses were performed in the UK Biobank and a prospective validation cohort. Mendelian randomisation (MR) analyses used genetic data derived from the UK Biobank, International Consortium for Blood Pressure, and COGENT consortium. Mendelian randomisation analysis identified a potentially adverse causal effect of higher systolic BP on cognitive function [−0.044 standard deviation (SD); 95% confidence interval (CI) −0.066, −0.021] with the MR estimate strengthening (−0.087 SD; 95% CI −0.132, −0.042), when further adjusted for diastolic BP. Mendelian randomisation analysis found 242, 168, and 68 IDPs showing significant (false discovery rate P < 0.05) association with systolic BP, diastolic BP, and pulse pressure, respectively. Most of these IDPs were inversely associated with cognitive function in observational analysis in the UK Biobank and showed concordant effects in the validation cohort. Mendelian randomisation analysis identified relationships between cognitive function and the nine of the systolic BP-associated IDPs, including the anterior thalamic radiation, anterior corona radiata, or external capsule. Conclusion Complementary MR and observational analyses identify brain structures associated with BP, which may be responsible for the adverse effects of hypertension on cognitive performance.

Background: Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited. Objectives: A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. Participants/methods: Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants. Results: HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides. Conclusion: HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations. publishedVersion

INTRODUCTIONStudies have suggested sleep duration may be associated with Alzheimer’s disease risk, but findings based on self-reported sleep duration are likely to be influenced by reverse causation and residual confounding bias.METHODSA polygenic score (PGS) for device-measured sleep duration was constructed using LDpred2-auto in 77,770 white British UK Biobank participants. We applied the PGS to 264,746 white British participants independent of the sample from which the PGS was developed. We assessed the association of fifths of genetically predicted sleep duration with Alzheimer’s disease risk (1,451 cases/264,746 individuals over median 12.5y of follow-up).RESULTSThe PGS explained ∼2% of variation in device-measured sleep duration. Compared to individuals in the middle fifth of PGS, those in the highest fifth (indicating ∼15 mins/day longer sleep) had a lower risk of Alzheimer’s disease (HR=0.79[95%CI,0.67-0.94]).DISCUSSIONOur results indicate that genetic predisposition to relatively long sleep duration is associated with a lower Alzheimer’s disease risk.

Despite early interest, the evidence linking fatty acids to cardiovascular diseases remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the aetiology of several cardiovascular disease endpoints in up to 1,153,768 European and 212,453 East Asian ancestry individuals. As instruments, we selected single nucleotide polymorphisms (SNP) mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple cardiovascular diseases, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low- density lipoprotein (LDL)-cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that genetically-determined PUFA and MUFA biosynthesis are involved in the aetiology of cardiovascular diseases and suggest LDL-cholesterol as a potential mediating trait between PUFA biosynthesis and cardiovascular diseases risk.

Objective: Depression and chronic widespread pain (CWP) frequently coexist, but whether depression is an independent causal risk factor for CWP, and/or vice versa, remains unclear. We investigated the bidirectional causal relationship between depression and CWP.Methods: We performed a two‐sample Mendelian randomization (MR) study to estimate the causal relationship between genetically predicted depression (170,756 cases, 329,443 controls) and risk of CWP (6,914 cases, 242,929 controls), and the effect of CWP on depression susceptibility, using large population level genetic data. We used a new MR method, Causal Analysis Using Summary Effect estimates (CAUSE), which allows for sample overlap, in addition to traditional MR and sensitivity analyses.Results: For each doubling in odds of genetic liability to depression, the risk of chronic widespread pain was increased (OR 1.004, 95% credible interval 1.003-1.005; p=7.3x10-5 that the causal model is a better fit than non-causal model). There was bidirectional evidence of causality, with genetic liability to chronic widespread pain increasing depression susceptibility (OR 2.31; 95%CrI 1.57, 3.40; p=0.0026 that the causal model is a better fit). Other MR methods produced concordant results.Conclusions: This study provides evidence in support of a bidirectional causal relationship between depression and increased risk of chronic widespread pain, whilst overcoming the major limitations of previous epidemiological studies. Interventions for depression may be an effective strategy to prevent or reduce the burden of chronic widespread pain and vice versa.

BackgroundKidney stone disease (KSD) is linked to obesity, metabolic syndrome and biochemical alterations including higher serum calcium concentration. The mechanisms by which these phenotypes associate with KSD are uncertain. We aimed to establish the effects of adiposity on KSD using conventional and genetic epidemiological techniques.MethodsWe assessed observational associations between measures of adiposity and incident KSD in 479,405 people from the UK Biobank. To facilitate Mendelian randomization (MR) analyses, we undertook genome-wide association studies (GWAS) of KSD in the UK Biobank in combined and sex-specific subsets. Univariable, multivariable and mediation MR analyses were used to calculate odds ratio (OR) or beta coefficient (ß) for risk of KSD per genetically instrumented higher marker of adiposity, metabolic syndrome parameter, biochemical phenotype, and inflammation and identify violations of MR assumptions.FindingsObservational analyses demonstrated that measures of central adiposity (waist-to-hip ratio (WHR) and waist circumference (WC)) are more strongly associated with incident KSD than measures of general adiposity (body mass index (BMI)). Three novel KSD-GWAS loci were identified (SLC2A12, TRPV5, and SLC28A1); no sex-specific loci were detected. MR analyses established that higher central adiposity is causally linked to both KSD and higher adjusted serum calcium concentrations independent of BMI (one standard deviation higher WHR: OR for KSD=1·43, p=4·1×10−6; ß for serum calcium concentration=0·11mmol/L, p=2·7×10−7). Mediation analyses indicated that 12% of the effect of WHR on KSD is due its role in elevating serum calcium concentration. Our MR studies indicated that other components of the metabolic syndrome, serum uric acid levels, and biomarkers of inflammation are unlikely to be implicated in the causation of KSD.InterpretationOur study indicates that visceral adipose depots elevate serum calcium concentration and cause an increased risk of KSD. Therapies targeting central adipose deposition may affect calcium homeostasis and have utility for the prevention of KSD.

Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology.

ObjectiveTo use the example of the effect of body mass index (BMI) on COVID-19 susceptibility and severity to illustrate methods to explore potential selection and misclassification bias in Mendelian randomisation (MR) of COVID-19 determinants.DesignTwo-sample MR analysis.SettingSummary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) and COVID-19 Host Genetics Initiative (HGI) consortia.Participants681,275 participants in GIANT and more than 2.5 million people from the COVID-19 HGI consortia.ExposureGenetically instrumented BMI.Main outcome measuresSeven case/control definitions for SARS-CoV-2 infection and COVID-19 severity: very severe respiratory confirmed COVID-19 vs not hospitalised COVID-19 (A1) and vs population (those who were never tested, tested negative or had unknown testing status (A2)); hospitalised COVID-19 vs not hospitalised COVID-19 (B1) and vs population (B2); COVID-19 vs lab/self-reported negative (C1) and vs population (C2); and predicted COVID-19 from self-reported symptoms vs predicted or self-reported non-COVID-19 (D1).ResultsWith the exception of A1 comparison, genetically higher BMI was associated with higher odds of COVID-19 in all comparison groups, with odds ratios (OR) ranging from 1.11 (95%CI: 0.94, 1.32) for D1 to 1.57 (95%CI: 1.57 (1.39, 1.78) for A2. As a method to assess selection bias, we found no strong evidence of an effect of COVID-19 on BMI in a ‘no-relevance’ analysis, in which COVID-19 was considered the exposure, although measured after BMI. We found evidence of genetic correlation between COVID-19 outcomes and potential predictors of selection determined a priori (smoking, education, and income), which could either indicate selection bias or a causal pathway to infection. Results from multivariable MR adjusting for these predictors of selection yielded similar results to the main analysis, suggesting the latter.ConclusionsWe have proposed a set of analyses for exploring potential selection and misclassification bias in MR studies of risk factors for SARS-CoV-2 infection and COVID-19 and demonstrated this with an illustrative example. Although selection by socioeconomic position and arelated traits is present, MR results are not substantially affected by selection/misclassification bias in our example. We recommend the methods we demonstrate, and provide detailed analytic code for their use, are used in MR studies assessing risk factors for COVID-19, and other MR studies where such biases are likely in the available data.SummaryWhat is already known on this topic-Mendelian randomisation (MR) studies have been conducted to investigate the potential causal relationship between body mass index (BMI) and COVID-19 susceptibility and severity.-There are several sources of selection (e.g. when only subgroups with specific characteristics are tested or respond to study questionnaires) and misclassification (e.g. those not tested are assumed not to have COVID-19) that could bias MR studies of risk factors for COVID-19.-Previous MR studies have not explored how selection and misclassification bias in the underlying genome-wide association studies could bias MR results.What this study adds-Using the most recent release of the COVID-19 Host Genetics Initiative data (with data up to June 2021), we demonstrate a potential causal effect of BMI on susceptibility to detected SARS-CoV-2 infection and on severe COVID-19 disease, and that these results are unlikely to be substantially biased due to selection and misclassification.-This conclusion is based on no evidence of an effect of COVID-19 on BMI (a ‘no-relevance control’ study, as BMI was measured before the COVID-19 pandemic) and finding genetic correlation between predictors of selection (e.g. socioeconomic position) and COVID-19 for which multivariable MR supported a role in causing susceptibility to infection.-We recommend studies use the set of analyses demonstrated here in future MR studies of COVID-19 risk factors, or other examples where selection bias is likely.

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10-31) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

We performed Mendelian randomization analyses of body mass index and waist–hip ratio adjusted for body mass index in Dupuytren’s disease using summary statistics from genome-wide association study meta-analyses. We found that adiposity is causally protective against Dupuytren’s disease, with the inverse-variance weighted Mendelian randomization analysis estimating that a 1 standard deviation increase in body mass index (equivalent to 4.8 kg/m2) leads to 28% (95% confidence interval: 18–37%) lower relative odds of developing Dupuytren’s disease, and a 1 standard deviation increase in waist–hip ratio adjusted for body mass index (equivalent to a waist–hip ratio of 0.09) leads to 26% (95% confidence interval: 6–42%) lower relative odds of developing Dupuytren’s disease. We conclude from this study that regardless of the well-established negative health effects of obesity, the raised body mass index is associated with a lower risk of Dupuytren’s disease and may be causally protective for the development of the disease.

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programmes showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of our approach in identifying and prioritising potential therapeutic targets.

ObjectiveThere is limited prospective evidence on the association of physical activity with hepatobiliary cancer subtypes and other major hepatobiliary diseases, especially in China. We aimed to quantify the associations with risk of these diseases.MethodsThe study population involved 460 937 participants of the prospective China Kadoorie Biobank aged 30–79 years from 10 diverse areas in China without history of cancer or hepatobiliary disease at baseline. Cox regression was used to estimate adjusted hazard ratios (HRs) for each disease associated with self-reported total and domain-specific physical activity (occupational and non-occupational, ie, leisure time, household and commuting).ResultsDuring ~10 years of follow-up, 22 012 incident cases of hepatobiliary diseases were recorded. The overall mean (SD) total physical activity was 21.2 (13.9) metabolic equivalent of task (MET)-hours/day, with 62% from occupational activity. Total physical activity was inversely associated with hospitalised non-alcoholic fatty liver disease (HR comparing top vs bottom quintile: 0.62, 95% confidence interval (CI) 0.53 to 0.72), viral hepatitis (0.73, 95% CI 0.62 to 0.87), cirrhosis (0.76, 95% CI 0.66 to 0.88) and liver cancer (0.81, 95% CI 0.71 to 0.93), as well as gallstone disease (0.86, 95% CI 0.81 to 0.90), gallbladder cancer (0.51, 95% CI 0.32 to 0.80) and biliary tract cancer (0.55, 95% CI 0.38 to 0.78). The associations for occupational physical activity were similar to those for total physical activity, but for non-occupational physical activity they differed by disease subtype. For leisure-time physical activity, there was an inverse association with liver cancer and an inverse trend for gallstone disease (HR comparing ≥7.5 MET-hours/day with none: 0.83, 95% CI 0.75 to 0.91 and 0.82, 95% CI 0.66 to 1.01).ConclusionAmong Chinese adults, high total physical activity, particularly occupational physical activity, was inversely associated with risk of major hepatobiliary cancers and diseases, including non-alcoholic fatty liver disease, cirrhosis and certain types of cancer.

Background . Ultrasound assessment of myocardial strain allows non-invasive identification of early stages of heart failure with preserved ventricular ejection fraction. A decline of the left ventricle (LV) global longitudinal strain in hypertension (HT) accompanied by LV hypertrophy (LVH) was reported in clinical samples with manifest HT. Data on the relationship between longitudinal strain and blood pressure (BP) and HT in general population is lacking. Objective . We studied the relationship between LV peak systolic global longitudinal strain ( GLS ) and strain rate ( GSR ) in subjects with high and controlled BP from a general population sample aged over 55 years. Design and methods . The cross-sectional study was based on a population cohort (HAPIEE, Novosibirsk). In a random sample (n = 416, aged 55–84 years old) we performed echocardiography and evaluated GLS and GSR of LV by speckle tracking technique. ANOVA multivariable models were applied. Results. In the studied sample, the prevalence of HT comprised 78,9 %. The mean GLS value was –18,7 ± 3,79 %, and it was lower in men than in women (–18,2 ± 3,85 % vs –19,2 ± 3,66 %, p = 0,005). The mean GSR value was –0,84 ± 0,17s –1 , and did not differ by sex. The absolute value of GLS in HT was lower than in normotensives: –18,5 ± 3,73 % vs –19,9 ± 3,42 %, p = 0,003; this difference was independent of age, sex and LV myocardial mass index (IMM), p = 0,011; but it was attenuated in a multivariable-adjusted model including body mass index (BMI). In HT groups, the GLS was the lowest among those “treated ineffectively” and significantly lower than in normotensives independently of age, sex and myocardium mass index (p = 0,008). The absolute value of GSR in HT was lower than in normotensives: –0,90 ± 0,17 s –1 vs –0,83 ± 0,17s –1 , p < 0,001; and persisted in multivariable models. GSR was the lowest among those “treated ineffectively” and significantly lower than in normotensives in multivariable models independently of age, sex, BMI and myocardial mass index (p = 0,017; 0,002). The average values of LV ejection fraction (Simpson) in all groups were above 50 % without significant inter-group differences (p = 0,904). conclusions. In the studied population sample, GLS and GSR of LV were associated with HT; however, the association between GLS and HT was largely explained by BMI. In hypertensives, the lowest GLS and GSR , as well as higher extent of LVH, were found among those treated ineffectively, which might point at the initial reduction of systolic ventricular function in HT with inadequate BP control.

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.

The mitochondrial DNA (mtDNA) copy number was analyzed via quantitative real-time PCR. A random subset of 996 people was studied (437 men with an average age of 67.3 ± 7.2 years and 559 women with an average age of 67.6 ± 7.1 years). They were selected from a population cohort of 9360 people who were initially examined in the international HAPIEE project (2003–2005, initial age of 45–69 years) in Novosibirsk. The participants were reexamined after 12 years in 2015–2017. The average relative mtDNA copy number in women was significantly higher than in men, regardless of age and smoking status, p = 0.001. The relative mtDNA copy number of blood leukocytes negatively correlated with age in men (p = 0.005) and women (p < 0.001). In the age-standardized analysis, the mtDNA copy number was negatively associated with waist and hip size and heart rate in people of both genders. Associations with some other indicators depend on gender. In women, the mtDNA copy number was negatively associated with the atherogenicity level, body mass indices, and blood glucose level and positively associated with HDL cholesterol. In men, the mtDNA copy number is positively related to the level of physical activity. Regardless of age, the average relative mtDNA copy number in peripheral blood leukocytes was higher in nonsmoking men than in smokers (p = 0.003). The mtDNA copy number was lower in women with diabetes mellitus than in women without it (p = 0.005). In both genders, people with an initial history of arterial hypertension had a lower mtDNA copy number in peripheral blood leukocytes after 12 years of observation than normotonics (p = 0.05). These results broadly support the hypothesis that the mtDNA copy number may act as a biomarker of age.

Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to 115,082 UK Biobank participants. Genetically predicted effects were generally consistent among drug targets, which were intended to modify the same lipoprotein lipid trait. For example, the linear fit for the MR estimates on all 249 metabolic traits for genetically predicted inhibition of LDL cholesterol lowering targets HMGCR and PCSK9 was r2 = 0.91. In contrast, comparisons between drug classes that were designed to modify discrete lipoprotein traits typically had very different effects on metabolic signatures (for instance, HMGCR versus each of the 4 triglyceride targets all had r2 < 0.02). Furthermore, we highlight this discrepancy for specific metabolic traits, for example, finding that LDL cholesterol lowering therapies typically had a weak effect on glycoprotein acetyls, a marker of inflammation, whereas triglyceride modifying therapies assessed provided evidence of a strong effect on lowering levels of this inflammatory biomarker. Our findings indicate that genetically predicted perturbations of these drug targets on the blood metabolome can drastically differ, despite largely consistent effects on risk of CAD, with potential implications for biomarkers in clinical development and measuring treatment response.

Publisher Copyright: © 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

Aims/hypothesisMetformin use has been associated with reduced incident dementia in diabetic patients in observational studies. However, the causality between the two in the general population is unclear. This study uses Mendelian randomization (MR) to investigate the causal effect of metformin targets on Alzheimer’s disease (AD) and potential causal mechanisms in the brain linking the two.MethodsGenetic proxies for the effects of metformin drug targets were identified as variants in the gene for the corresponding target that associated with HbA1c level (N=344,182) and expression level of the corresponding gene (N≤31,684). The cognitive outcomes were derived from genome-wide association studies comprising of 527,138 middle-aged Europeans, including 71,880 AD or AD-by-proxy patients. MR estimates representing lifelong metformin use on AD and cognitive function in the general population were generated. Effect of expression level of 22 metformin-related genes in brain cortex (N=6,601 donors) on AD was further estimated.ResultsGenetically proxied metformin use equivalent to a 6.75 mmol/mol (1.09%) reduction of HbA1c was associated with 4% lower odds of AD (odds ratio [OR]=0.964, 95%CI=0.982∼0.946, P=1.06×10−4) in non-diabetic individuals. One metformin target, mitochondrial complex 1 (MCI), showed a robust effect on AD (OR=0.88, P=4.73×10−4) that was independent of AMPK. MR of expression in brain cortex tissue showed that decreased MCI-related gene, NDUFA2, expression was associated with reduced AD risk (OR=0.95, P=4.64×10−4) and less cognitive decline.Conclusion/interpretationMetformin use is likely to cause reduced AD risk in the general population. Mitochondrial function and the NDUFA2 gene are likely mechanisms of action in dementia protection.Research in contextWhat is already known about this subjectMetformin is an anti-diabetic drug with repurposing potential for dementia prevention.In a search of PubMed, Embase and clinicaltrials.gov, a few observational studies suggested the association of metformin use with reduced dementia incidence in diabetic patientsWhat is the key question?What is the effect of genetically proxied metformin use on Alzheimer’s disease (AD) and cognitive function in the general population, especially for those without diabetes? Is the causal role between the two at least partly influenced by mechanisms in the brain?What are the new findings?In a Mendelian randomization analysis of over 527,138 individuals (71,880 AD or AD-by-proxy cases), genetically proxied metformin use equivalent to a 6.75 mmol/mol (1.09%) reduction of HbA1c was associated with 14% lower odds of AD (odds ratio=0.86), where mitochondrial complex I is a key effect modifier.Expression level of a mitochondrial complex I related gene, NDUFA2, showed an effect on reducing AD risk and less cognitive decline in brain.How might this impact on clinical practice in the foreseeable future?Our study predicts the efficacy of metformin on reducing AD risk and reducing cognitive decline in the general population, especially for those without diabetes.Mitochondrial function and a mitochondrial related gene, NDUFA2, could be considered as a novel drug target for dementia prevention.Graphical abstractTweet Effect of metformin targets reduced 4% of Alzheimer’s disease risk in non-diabetic individuals. @oldz84 @tomgaunt @mendel_random @mrc_ieu

Aims Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. Our objective was to examine if modifiable anthropometric obesity indices show putatively causal association with kidney health and disease and highlight biological mechanisms of potential relevance to the association between obesity and the kidney. Methods and results We performed observational, one-sample, two-sample Mendelian randomization (MR) and multivariable MR studies in ∼300 000 participants of white-British ancestry from UK Biobank and participants of predominantly European ancestry from genome-wide association studies. The MR analyses revealed that increasing values of genetically predicted body mass index and waist circumference were causally associated with biochemical indices of renal function, kidney health index (a composite renal outcome derived from blood biochemistry, urine analysis, and International Classification of Disease-based kidney disease diagnoses), and both acute and chronic kidney diseases of different aetiologies including hypertensive renal disease and diabetic nephropathy. Approximately 13–16% and 21–26% of the potentially causal effect of obesity indices on kidney health were mediated by blood pressure and type 2 diabetes, respectively. A total of 61 pathways mapping primarily onto transcriptional/translational regulation, innate and adaptive immunity, and extracellular matrix and metabolism were associated with obesity measures in gene set enrichment analysis in up to 467 kidney transcriptomes. Conclusions Our data show that a putatively causal association of obesity with renal health is largely independent of blood pressure and type 2 diabetes and uncover the signatures of obesity on the transcriptome of human kidney.

Triangulation of evidence from clinical trials and human genetics suggests a potential excess risk of cardiovascular disease events arising from therapeutic inhibition of sclerostin.

Polygenic risk scores (PRS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease. In this study, we have constructed an atlas of associations between 129 different PRS and 249 circulating metabolites in up to 83,004 participants from the UK Biobank study. As an exemplar to demonstrate the value of this atlas we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bi-directional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as body mass index (Beta=0.16 per standard deviation change in GlycA, 95% CI=0.11 to 0.21, P=9.9×10−10) or liability towards smoking cigarettes (Beta=0.28, 95% CI=0.20 to 0.35, P=2.4×10−14), on systemic inflammation as opposed to the converse direction of effect. Furthermore, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PRS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. All results can be visualised athttp://mrcieu.mrsoftware.org/metabolites_PRS_atlas.